ConLogAI – Concept for an AI-enabled platform for construction logistics scheduling

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Gehring, Maximilian and Brötzmann, Jascha and Rüppel, Uwe; Moreno-Rangel, Alejandro and Kumar, Bimal, eds. (2025) ConLogAI – Concept for an AI-enabled platform for construction logistics scheduling. In: EG-ICE 2025. University of Strathclyde Publishing, GBR, pp. 527-535. ISBN 9781914241826 (https://doi.org/10.17868/strath.00093231)

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Abstract

Construction logistics management plays a crucial role in the successful execution of construction projects. Building Information Modeling (BIM) supports scheduling processes by providing structured project data. The integration of Artificial Intelligence (AI) further enhances the impact of BIM by enabling automation, pattern recognition, and intelligent decision-making. Additionally, digital technologies such as the Internet of Things (IoT) can support data-driven adaptations during execution. This paper introduces a concept for a BIM-based, AI-enabled construction scheduling platform designed to address critical challenges in construction logistics planning. By leveraging BIM data as a foundation, the platform incorporates AI-driven semantic enrichment to derive task relationships and dependencies, while employing advanced scheduling algorithms to generate optimized execution plans. The proposed system aims to enable dynamic, resource-constrained scheduling and facilitate real-time adaptation to disruptions. A preliminary implementation validates the feasibility of the concept and highlights its potential to improve transparency, efficiency, and responsiveness in construction logistics management.

  • Item type:Book Section
    ID code:93231
    Dates:
    Date
    Event
    1 July 2025
    Published
    9 June 2025
    Accepted
    Subjects:Fine Arts > Architecture
    Department:Faculty of Engineering > Architecture
    Depositing user: Pure Administrator
    Date deposited:26 Jun 2025 15:07
    Last modified:04 Apr 2026 00:19
    URI:https://strathprints.strath.ac.uk/id/eprint/93231
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